Collision avoidance in a distributed tokenization environment

ABSTRACT

A client receives sensitive data to be tokenized. The client queries a token table with a portion of the sensitive data to determine if the token table includes a token mapped to the value of the portion of the sensitive data. If the mapping table does not include a token mapped to the value of the portion of the sensitive data, a candidate token is generated. The client queries a central token management system to determine if the candidate token collides with a token generated by or stored at another client. In some embodiments, the candidate token includes a value from a unique set of values assigned by the central token management system to the client, guaranteeing that the candidate token does not cause a collision. The client then tokenizes the sensitive data with the candidate token and stores the candidate token in the token table.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/080,589, filed Mar. 25, 2016, now U.S. Pat. No. ______, which is acontinuation of U.S. application Ser. No. 14/042,325, filed Sep. 30,2013, now U.S. Pat. No. 9,313,195, which is incorporated by reference inits entirety.

FIELD OF ART

This application relates to the field of data protection, and morespecifically to the protection of information using dynamictokenization.

BACKGROUND

Many websites, services, and applications implement various dataprotection techniques. Certain techniques involve the use of anencryption key or password that can be subject to interception or bruteforce guessing. Other methods may protect data but require extensivecomputing resources to encode and decode data. Such methods often failto utilize various data format advantages when protecting the data.Often, distinct systems implementing data protection techniques arerequired to store information associated with the protected data withindistinct repositories or databases. Thus, it may be advantageous toimplement data protection techniques that utilize distinct informationstorage locations in such a way as to minimize the processing andstorage burden across a data protection system as a whole whileimproving security and tracking potential data use information andcollisions.

SUMMARY

A central token management system manages tokens generated by clients ina distributed tokenization environment to avoid collisions betweentokens generated by different clients.

A client receives sensitive data to be tokenized. A token tableassociated with the client is queried with a portion of the sensitivedata. If the token table includes a token mapped to the sensitive data,the token is returned and used to tokenize the sensitive data. Otherwiseif the token table does not include a token mapped to the value of theportion of the sensitive data, the client generates a candidate token.When generating new entries tokens in a distributed tokenizationenvironment, collisions between tokens generated by different clients inthe distributed tokenization environment should be avoided.

One way in which collision avoidance can be implemented is through theuse of a central token management system to determine whether agenerated candidate token causes a collision with a token generated byor stored at another client. Before the candidate token is used totokenize the received data, the client determines whether the candidateobtained token causes a collision with tokens generated by otherclients. The client queries a central token management system todetermine if a collision exists between the candidate token and tokensgenerated by other clients. If the candidate token does not cause acollision, the candidate token is used to tokenize the received data,the client stores the candidate token in the token table, and the clientsends the candidate token to the central token management system so thatother clients do not generate tokens that collide with the candidatetoken.

If the candidate token does cause a collision with a token generated byanother client, a new candidate token is generated, and a determinationof whether the new candidate token causes a collision with tokensgenerated by other clients is made. This process can be repeated until atoken is generated that does not cause a collision with any of thetokens generated by other clients.

Another way token collision avoidance can be implemented is byrestricting the tokens each client can generate to a set of valuesunique to each client. In some embodiments, the central token managementsystem assigns each client a unique range or set of candidate tokenvalues. For example, the central token management system may assign eachclient a unique numeric seed value, and can assign each client a rangeof values beginning with the unique numeric seed value. In suchembodiments, when a client receives sensitive data to be tokenized, andthe client determines that a token table associated with the client doesnot include a token mapped to the value of a portion of the data, theclient can generate a candidate token within the range of candidatetoken values assigned to the client.

As the range of candidate token values assigned to the client is uniqueto the client, the generated candidate token will not cause a collisionwith tokens generated by the other clients assigned a unique range ofcandidate token values by the central token management system.

Accordingly, the client can tokenize the sensitive data with thegenerated token, can store the generated token in the token tableassociated with the client, and can provide the generated token to thecentral token management system for subsequent token use analysis andtracking.

BRIEF DESCRIPTION OF DRAWINGS

The disclosed embodiments have other advantages and features which willbe more readily apparent from the detailed description, the appendedclaims, and the accompanying figures (or drawings). A brief introductionof the figures is below.

FIG. 1 is a system diagram for a distributed tokenization environment,according to one embodiment.

FIG. 2 illustrates data flow within a tokenization system, according toone embodiment.

FIG. 3 illustrates a diagram of a distributed tokenization environment,according to one embodiment.

FIG. 4 illustrates a flow diagram of a process for avoiding tokencollisions in a distributed tokenization environment by using a centraltoken management system, according to one embodiment.

FIG. 5 illustrates a flow diagram of a process for avoiding tokencollisions in a distributed tokenization environment by restrictingvalues for candidate tokens to a set of values unique to each client,according to one embodiment.

The figures (Figs.) depict embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdescription that alternative embodiments of the structures and methodsillustrated herein can be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION

Reference will now be made in detail to several embodiments, examples ofwhich are illustrated in the accompanying figures. It is noted thatwherever practicable, similar or like reference numbers can be used inthe figures and can indicate similar or like functionality. The figuresdepict embodiments of the disclosed system (or method) for purposes ofillustration only. One skilled in the art will readily recognize fromthe following description that alternative embodiments of the structuresand methods illustrated herein can be employed without departing fromthe principles described herein.

Tokenization Overview

The transmission and storage of sensitive data, such as passwords,credit card numbers, social security numbers, bank account numbers,driving license numbers, transaction information, date information, etc,can be challenging. Before sensitive data can be transmitted or stored,the sensitive data can be tokenized into tokenized data to prevent anunauthorized entity from accessing the data.

As used herein, the tokenization of data refers to the generation oftokenized data by querying one or more token tables mapping input valuesto tokens with the one or more portions of the data, and replacing thequeried portions of the data with the resulting tokens from the tokentables. Tokenization can be combined with encryption for increasedsecurity, for example by encrypting sensitive data using amathematically reversible cryptographic function (e.g.,datatype-preserving encryption or DTP), a one-way non-reversiblecryptographic function (e.g., a hash function with strong, secret salt),or a similar encryption before or after the tokenization of thesensitive data. Any suitable type of encryption can be used in thetokenization of data. A detailed explanation of the tokenization processcan be found in U.S. patent application Ser. No. 13/595,439, filed Aug.27, 2012, which is hereby incorporated by reference.

As used herein, the term token refers to a string of characters mappedto an input string of characters in a token table, used as a substitutefor the string of characters in the creation of tokenized data. A tokencan have the same number of characters as the string being replaced, orcan have a different number of characters. Further, the token can havecharacters of the same type (such as numeric, symbolic, or alphanumericcharacters) as the string of characters being replaced or characters ofa different type.

Any type of tokenization can be used to perform the functionalitiesdescribed herein. One such type of tokenization is static lookup table(“SLT”) tokenization. SLT tokenization maps each possible input values(e.g., possible character combinations of a string of characters) to aparticular token. An SLT includes a first column comprising permutationsof input string values, and can include every possible input stringvalue. The second column of an SLT includes tokens, with each associatedwith an input string value of the first column. Each token in the secondcolumn can be unique among the tokens in the second column. Optionally,the SLT can also include one or several additional columns withadditional tokens mapped to the input string values of the first column.

In some embodiments, to increase the security of tokenization, sensitivedata can be tokenized two or more times using the same or additionaltoken tables. For example, the first 8 digits of a 16 digit credit cardnumber can be tokenized with an 8 digit token table to form firsttokenized data, and the last 12 digits of the first tokenized data canbe tokenized using a 12 digit token table to form second tokenized data.In another example, the first 4 digits of a credit card number aretokenized using a first token table, the second 4 digits are tokenizedwith a second token table, the third 4 digits are tokenized with a thirdtoken table, and the last 4 digits are tokenized with a fourth tokentable. Certain sections of the sensitive data can also be leftun-tokenized; thus a first subset of the resulting tokenized data cancontain portions of the sensitive data and a second subset of thetokenized data can contain a tokenized version of the sensitive data.

Dynamic token lookup table (“DLT”) tokenization operates similarly toSLT tokenization, but instead of using static tables for multipletokenizations, a new token value is generated and included in a tokentable entry each time sensitive data is tokenized. The new token valuecan be generated randomly, can be randomly selected from among a set ofvalues, or can be generated via any other suitable means. A seed valuecan be used to generate token values, to select a set of values fromwhich to select a token value from among multiple sets of values, or torandomly select a value from among a set of values for use as the tokenvalue. It should be noted that as used herein, “randomly” can refer topseudo-randomly or substantially randomly. The seed value can include aportion of data being tokenized.

In some embodiments, a DLT can map portions of sensitive data beingreplaced by a token to a token. The DLT can include the entire sensitivedata (including portions of the sensitive data that are not replaced bya token), and the DLT can indicate the portion of the sensitive databeing replaced by the token and can map the portion to the token. DLTscan in some configurations provide a higher level of security comparedto SLT but require the storage and/or transmission of a large amount ofdata associated with each of the generated token tables. It should benoted that DLT tokenization can be used to tokenize data according tothe principles described above with regards to SLT tokenization.

The security of tokenization can be further increased through the use ofinitialization vectors (“IVs”). An initialization vector is a string ofdata used to modify sensitive data prior to tokenizing the sensitivedata. Example sensitive data modification operations include performinglinear or modulus addition on the IV and the sensitive data, performinglogical operations on the sensitive data with the IV, encrypting thesensitive data using the IV as an encryption key, and the like. The IVcan be a portion of the sensitive data. For example, for a 12-digitnumber, the last 4 digits can be used as an IV to modify the first 8digits before tokenization. IVs can also be retrieved from an IV table,received from an external entity configured to provide IVs for use intokenization, or can be generated based on, for instance, the identityof a user, the date/time of a requested tokenization operation, based onvarious tokenization parameters, and the like. Data modified by one ormore IVs that is subsequently tokenized includes an extra layer ofsecurity—an unauthorized party that gains access to the token tablesused to tokenized the modified data will be able to detokenize thetokenized data, but will be unable to de-modify the modified datawithout access to the IVs used to modify the data.

To detokenize tokenized data, a portion of the tokenized data includinga token is used to query a token table, and a value mapped to the tokenwithin the token table is used to replace the portion of the tokenizeddata including the token. If multiple values are mapped to the sametoken, a detokenization system will be unable to identify which valuemapped to the token to use in detokenizing the tokenized data. More thanone value mapped within a token table or within a distributedtokenization environment is referred to herein as a “token collision”.

For instance, the values “123456 123456 1234” and “45678 45678 1234” areeach mapped within a token table to the token “95173 95173 1234”, thenwhen detokenizing the tokenized data “95173 95173 1234”, adetokenization system will be unable to select between the value “123456123456 1234” and “45678 45678 1234”. As a result, the sensitive datarepresented by the tokenized data “95173 95173 1234” is irrecoverable.

In a distributed tokenization environment, such as the environments ofFIGS. 1 and 3, each client 100 can generate and store a set of tokens.If, within the distributed tokenization environment, more than one setof tokens stored by the clients include a particular token, a potentialtoken collision exists within the distributed tokenization environment.

Tokenization System Overview

FIG. 1 is a system diagram for a distributed tokenization environment,according to one embodiment. The environment of FIG. 1 includes aplurality of clients 100A, 100B, and 100C (“clients 100” hereinafter),and a central token management system 110, communicatively coupled via anetwork 105. Each client 100 can be a retailer, business, or otherorganization, though it should be noted that clients can also beindividual users or any other suitable entity. An entity can receivesensitive data, for instance a credit card number or other accountnumber during the course of a transaction with a user, and tokenize allor part of the sensitive data, for instance prior to storage ortransmission. It should be noted that while three clients 100 areillustrated in the embodiment of FIG. 1, other embodiments of the systemenvironment can contain any number of clients and/or other components.

A client 100 can include a computing device capable of processing dataas well as transmitting data to and receiving data from the othermodules of FIG. 1 via the network 105. For example, the client caninclude a desktop computer, laptop computer, smart phone, tabletcomputing device, server, payment terminal, or any other device havingcomputing and data communication capabilities. Each computing deviceincludes one or more processors, memory, storage, and networkingcomponents. Each client is coupled to the network and can interact withother modules coupled to the network using software such as a webbrowser or other application with communication functionality. Suchsoftware can include an interface for communicating with the othermodules via the network.

The network 105 connecting the various modules is typically theInternet, but can be any network, including but not limited to a localarea network (LAN), metropolitan area network (MAN), wide area network(WAN), cellular network, wired network, wireless network, privatenetwork, virtual private network (VPN), direct communication line, andthe like. The network can also be a combination of multiple differentnetworks.

Each client 100 in the embodiment of FIG. 1 includes an interface module120, a tokenization module 125, a token generation module 130, a tokentable 135, and a tokenized data module 140. The interface module 120 isconfigured to provide an interface between entities external to theclient and modules within the client. For instance, the interface modulecan provide an interface prompting a customer to swipe a credit card,and can transfer the credit card number received in response to thetokenization module 125 for tokenization. The interface module canprovide a graphic user interface (GUI) to entities external the client(for instance, via a display or a web page), and/or can provide acommunicative interface configured to automatically route receivedsensitive data. The interface module 120 can also provide an interfacefor communications between modules of the client, for instance routinggenerated tokens to the token tables storage module and tokenized datato the tokenized data storage module. The interface module 120 can alsoreceive requests for information associated with token tables stored inthe token tables storage module from the central token management system110, can query the token tables storage module in response, and canprovide information received in response to the query to the centraltoken management system.

The tokenization module 125 is configured to receive sensitive data, totokenize all or part of the received sensitive data, and to store ortransmit the tokenized data. In the embodiments described herein, thetokenization module 125 performs DLT tokenization, though it should benoted that other forms of tokenization can also be performed accordingto the principles described herein. The tokenization module 125 selectsa portion of the sensitive data to tokenize, and queries the token table135 to determine if the token table includes a token mapped to the valueof the portion of the sensitive data. In response to the token tableincluding such a token, the tokenization module 125 can tokenize thesensitive data with the token, for instance by replacing the portion ofthe sensitive data with the token.

In response to a determination that the token table 135 does not includea token mapped to the value of the portion of the sensitive data, thetokenization module 125 requests a token from the token generationmodule 130. The token generation module 130 is configured to generate arandom token value, for example by randomly selecting a token from a setof pre-generated token values, requesting and receiving a token from anexternal entity (such as the central token management system 110), orcan generate a token via any other suitable token generation means, suchas a token generation function. As noted above, the token generationmodule 130 can receive a seed value, such as an initialization vector,for use in generating or selecting a token. The seed value can include aportion of the sensitive data, or can be associated with the context ofthe tokenization operation (for instance, the identity of a user of theclient 100A, the time/date of the tokenization request, and the like).

Upon receiving the generated candidate token, the tokenization module125 determines whether a collision exists between the candidate tokenand a token generated by another client coupled to the central tokenmanagement system 110. The tokenization module 125 can query the centraltoken management system 110 with the candidate token, and in response,the central token management system 110 can determine if the value ofthe candidate token is equivalent to the value of a token generated byanother client or stored in the token table of another client. In someembodiments, the central token management system 110 queries each clientwith the candidate token, and each client informs the central tokenmanagement system 110 of whether a collision exists between thecandidate token and a token stored at the client. In other embodiments,the central token management system 110 stores a copy (or other indicia,e.g., a hash value) of each token generated by or stored at each clientin a master token table or token tables, and the central tokenmanagement system makes a determination of whether the candidate tokencauses a collision by querying the master token table or token tableswith the candidate token or indicia, and provides a response to thetoken management system 110 indicating the result of the determination.In response to a determination from the token management system 110 thatthe candidate token causes a collision with another token generated byor stored at another client, the tokenization module 125 can request anew candidate token from the token generation module 130, and theprocess of determining whether the new candidate token causes acollision is repeated until a candidate token that does not cause acollision is generated. Otherwise, where the token management system 110indicates that token does not cause a collision, the tokenization module125 uses the token to tokenize the sensitive data, and returns thetokenized data to the interface module 120.

It should be noted that in embodiments described further herein, thetoken generation module 130 generates or selects a candidate token fromamong a set of potential candidate token values unique to the client100A. For instance, the central token management system can assign aunique set of potential candidate token values to each client, using anidentifier value for the client as a starting point for a range of tokenvalues. For example, for a client associated with the unique identifier“01”, the central token management system can assign the client the setof potential candidate token values ranging from “01 000 000” to “01 999999”, and for a client associated with the unique identifier “36”, thecentral token management system can assign the client the set ofpotential candidate token values ranging from “36 000 000” to “36 999999”. In such embodiments, since the potential range of candidate tokenvalues is unique to each client, the candidate token generated by thetoken generation module 130 is unique to the client 100A, and does notcause a collision with a token generated by or stored at another client.

After the receiving a candidate token from the token generation module130 and determining that the token does not cause a collision with atoken generated by or stored at another client, the tokenization module125 can tokenize the sensitive data with the token. For instance, thetokenization module 125 can replace the selected portion of thesensitive data with the received token to form tokenized data. Forinstance, if the middle eight digits of a credit card number “1234 56789012 3456”, and the generated token is “99887766”, the tokenizationmodule 125 can replace the middle eight digits with the token to formthe tokenized data “1234 9988 7766 3456”. The tokenization module 125can store the received token and the association between the token andthe value of the replaced portion of sensitive data in the token table135. Continuing with the previous example, the tokenization module canstore a mapping between the value “56789012” and the token “99887766” inthe token table 135.

After tokenizing the sensitive data, the tokenization module 125 canstore the sensitive data in the tokenized data storage module 140, orcan transmit the tokenized data to an external entity (such as a bank,payment processor, retailer, financial institution, and the like).Although not described further herein, tokenized data can besubsequently accessed, for instance from the tokenized data storagemodule 140. The tokenized data can be detokenized by accessing the tokenused to tokenized the data from the token table 135, and replacing theportion of the tokenized data that includes the token with the valuemapped to the token within the token table to form detokenized data.

The central token management system 110 can interface with the clients100 to perform a variety of pre- and post-tokenization operations. Forinstance, the central token management system 110 can track and/or storetokens stored within token tables at each client within a master tokentable or token tables. Each time a client generates a new token, theclient can provide the new token to the central token management system110, and the central token management system can update the master tokentable or token tables to include the new token. The central tokenmanagement system 110 can be queried by a client to determine if a newlygenerated token collides with a token generated by or stored at anotherclient. The central token management system 110 can also track duplicatetokens (different tokens in different token tables at different clientsmapped to the same data portion value), and can store the duplicatetokens and associated information for subsequent auditing/analysis. Insome embodiments, instead of storing duplicate tokens, a hashrepresentative of each token or a reference to a token table is storedat the central token management system 110. The central token managementsystem 110 can also synchronize tokens stored within token tables atdifferent clients, and can track where each token is created, thecircumstances of the creation of the token, the use of each token, andany other information associated with the tokens, the clients, ortokenization operations. As noted above, the central token managementsystem 110 can assign a unique set of potential candidate token valuesto each client. Accordingly, when generating a new candidate token, eachclient can be configured to generate a candidate token value within theset of potential candidate token values such that each new candidatetoken generated by a client will not cause collisions with tokensgenerated by or stored at another client.

FIG. 2 illustrates an example data flow within the tokenization systemof FIG. 1, according to one embodiment. The tokenization module 125receives sensitive data 200. In FIG. 2, the sensitive data 200 includesthe string “123456 123456 1234”, which includes two segments, a firstsegment (the “tokenizing segment” 203) that includes the value “123456123456,” and a second segment (the “clear segment” 201) that includesthe value “1234.” The clear segment 201 can be used to select a tokentable from among a plurality of token tables, can be used to modify thetokenizing segment 203, can be used to query an IV table to retrieve anIV for use in tokenization, or can be used for any other suitablepurpose within the context of the tokenization operations describedherein.

The tokenization module 125 queries the token table 135 with the valueof the tokenizing segment 203. If the token table 135 includes a tokenmapped to the value of the tokenizing segment 203, the token table 135outputs the token to the tokenization module 125. The tokenizationmodule 125 tokenizes the sensitive data 200 using the token, forinstance by replacing the tokenizing segment 203 with the token, to formtokenized data. In FIG. 2, the value of the tokenizing segment, “123456123456” is mapped to the token “753951 456852”, and the value of thetokenized data is the “753951 456852”.

If the token table 135 does not include a token mapped to the value ofthe tokenizing segment 203, the tokenization module requests andreceives a candidate token from the token generation module 130. Inresponse to receiving the candidate token from the token generationmodule 130, the tokenization module 125 determines if a collision existsbetween the candidate token and a token generated at or stored byanother client. To do so, the tokenization module 125 can query acentral token management system 110 with the candidate token, and thecentral token management system can determine if the candidate tokencauses a collision with another token generated by or stored at anotherclient communicatively coupled to the central token management system.If the candidate token does cause a collision, the tokenization module125 can request a new candidate token, and the process can be repeateduntil a candidate token is received that does not cause a collision.Upon receiving a candidate token that does not cause a collision, thetokenization module 125 can tokenize the sensitive data with thecandidate token, and can store the candidate token and the associationbetween the candidate token and the value of the tokenizing segment 203in the token table 135.

As discussed above, in embodiments where the central token managementsystem 110 provides a unique set of potential candidate token values toeach client, the token generation module 130 can generate a candidatetoken having a value within an assigned unique set of potentialcandidate token values, guaranteeing that the candidate token will notcause a collision with a token generated by or stored at another client,and precluding the need for the tokenization module 125 to check forcollisions.

FIG. 3 illustrates a system diagram for a distributed tokenizationenvironment, according to one embodiment. The environment of FIG. 3includes a first user 150A and a second user 150B. The first user 150Auses client 100A to tokenize and detokenize sensitive data. The seconduse 150B uses client 100B to tokenize and detokenize sensitive data. Insome embodiments, user 150A and user 150B communicate with each othervia the network 105. For instance, user 150A may use client 100A totokenize sensitive data, and to send the tokenized data to user 150B.User 150B receives the tokenized data and detokenizes the tokenized datausing client 100B to obtain the sensitive data. It should be noted thatUser 150A and User 150B can refer to people, businesses, entities, orthe like.

Since user 150B uses client 100B to detokenize the tokenized datatokenized by client 100A, the token table 135B of client 100B may notinitially include a token used by the client 100A to tokenize thesensitive data and required by client 100B to detokenize the tokenizeddata. Client 100B can query the central token management system 110 todetermine if another client 100 stores the token required to detokenizethe tokenized data. In response, the central token management system 110determines that the token table 135A of client 100A includes the tokenused to tokenize the data. In some embodiments, the central tokenmanagement system 110 sends a response to client 100B notifying client100B that the client 100A stores the required token, and client 100B canrequest the required token directly from client 100A. In otherembodiments, the central token management system 110 acquires therequired token from the client 100A and provides the required token tothe client 100B. Upon receiving the required token, the client 100Bdetokenizes the tokenized data and can store the required token in thetoken table 135B.

Collision Avoidance Through Central Token Management

Token collision avoidance can be implemented within a distributedtokenization environment through the use of a central token managementsystem 110. The central token management system 110 can maintain amaster token table storing tokens generated by different clients 100communicatively coupled to the central token management system, or canbe configured to query the coupled clients to identify potentialcollisions with tokens stored by the clients. When a client generates anew candidate token, the client can query the central token managementsystem 110 to determine if the newly generated token causes a collisionwith a token from another client. If a client determines (for instance,based on feedback from the central token management system) that thecandidate token causes a collision with another token within thedistributed tokenization environment, the client can generate adifferent candidate token until a candidate token that does not cause acollision is generated.

FIG. 4 illustrates a flow diagram of a process for avoiding tokencollisions in a distributed tokenization environment by using a centraltoken management system, according to one embodiment. The client 100Agenerates 410 a candidate token and queries 420 the central tokenmanagement system 110 to determine if the candidate token causes acollision with token generated at or stored by any other clientcommunicatively coupled to the central token management system. Thecentral token management system 110 receives the request and determines430 if the candidate token causes a collision. As noted above, thecentral token management system 110 can search a master token tablestoring tokens generated by other clients in the distributedtokenization environment for a token equivalent to the candidate tokento determine if the candidate token causes a collision. Alternatively,the central token management system 100 can query other clients with thecandidate token to determine if any client stores a token equivalent tothe candidate token.

If the central token management system 110 determines that the candidatetoken does not cause a collision, a response is sent 450 to the client100A indicating that the candidate token does not cause a collision withany tokens generated by or stored at any other client in thetokenization system. The client 110A can then tokenize 455 sensitivedata using the candidate token, and can store the candidate token in atoken table associated with the client 100A. In addition, the client100A can provide the candidate token to the central token managementsystem 110 for inclusion in the master token table stored by the centraltoken management system 110 for subsequent use in collisiondeterminations with future candidate tokens generated by other clients.

If the central token management system 110 determines that the candidatetoken causes a collision, a response is sent 440 to the client 100Aindicating that the candidate token causes a collision with tokengenerated by or stored at another client. In response, the client 100Agenerates 445 a new candidate token, and the central token managementsystem is queried 420 with the new candidate token to determine if thenew candidate token causes a collision. This process is repeated until acandidate token generated that does not cause collisions with tokensgenerated by or stored at other clients in the distributed tokenizationenvironment.

It should be noted when determining if a candidate token causes acollision, additional information can be considered. For instance, if atoken table stores tokens, portions of sensitive data to which thetokens are mapped, and a clear text portion of sensitive data that isnot replaced with a token, the clear text portion can be used as anindex in determining if a token causes a collision. For example, for asensitive data string “123456 789012 3456”, a first client can generatea token “753951 924641”, and can store an association between thesensitive data portion “123456 789012”, the token “753951 924641”, andthe last four digits “3456” as a clear text index in a token tableassociated with the first client. Continuing with this example, for asensitive data string “098765 432109 8765”, a second client can generatethe same candidate token “753951 924641”, and can query the centraltoken management system 110 with the candidate token and the last fourdigits “8765” as a clear text index. Although the candidate token is thesame as the token previously generated by the first client, because theclear text index is different, the central token management system 110is able to distinguish between the candidate token and the token, andthe candidate token does not cause a collision within the distributedtokenization environment.

Collision Avoidance By Restricting Allowed Tokens

Token collision avoidance can be implemented within a distributedtokenization system by restricting the values of tokens that each clientin the distributed tokenization environment can generate. For instance,a client 100A can be limited to generating tokens that start with thevalue “01”, a client 100B can be limited to generating tokens that startwith the value “02”, and a client 100C can be limited to generatingtokens that start with the value “03.” Since client 100B and client 100Ccannot generate tokens that start with “01,” tokens generated by client100B and client 100C will not collide with tokens generated by client100A.

Restricting the tokens generated by clients can be implemented in manydifferent ways. For example, tokens can be restricted to starting with aspecific value, ending with a specific value, or including a specificvalue in the middle of the token. In some embodiments, each client in adistributed tokenization environment is associated with a uniqueidentifier, and the tokens generated by each client are restricted tovalues that begin with, end with, or include the unique identifier.Alternatively, an algorithm used to generate tokens can be designed suchthat tokens generated by different clients do not collide.

Restricting the tokens a client can generate enables the client togenerate candidate tokens even during times when the client cannot querythe central token management system 110 to determine if a candidatetoken causes a collision within the distributed tokenizationenvironment. For instance, if the central token management system 110 isoffline, is busy and/or irresponsive, or if time constraints prohibitwaiting for the central token management system 110 to respond to acollision query, a client can generate a token unique to the client,guaranteeing that the token does not cause a collision without requiringthe client to query the central token management system.

In one embodiment, the central token management system 110 assigns eachclient in the distributed tokenization environment a unique range or setof allowable token values. For example, the central token managementsystem 110 can assign a client 100A a set of possible token values thatare 8 digits long and that start with the value“21”. As a result, theclient 100A can only generate tokens that fall between the range“21000000” and “21999999”. Similarly, the central token managementsystem 110 can assign a client 100B a set of possible token values thatare 8 digits long and that start with the value “33”. As a result, theclient 110B can only generate tokens that fall between the range“33000000” and “33999999”. Accordingly, any token generated by theclient 100A will not collide with any token generated by the client100B, and vice versa. If a client generates one token for each value inthe set of possible token values assigned by the central tokenmanagement system 110, the client can request additional possible tokenvalues from the central token management system. Continuing with theprevious example, if the client 100A requests additional possible tokenvalues, the central token management system 110 can assign the client100A an additional set of possible token values that are 8 digits longand that start with the value “46”.

FIG. 5 illustrates a flow diagram of a process for avoiding tokencollisions in a distributed tokenization environment by restrictingvalues for candidate tokens to a set of values unique to each client,according to one embodiment. A client 100A requests 510 a unique set ofallowable token values from a central token management system 110. Therequest may be sent, for instance, during the initialization of client100A or responsive to receiving sensitive data to be tokenized. Thecentral token management system 110 receives the request and generates520 a set of allowable token values unique to the client 100A. In someembodiments, the central token management system 110 queries otherclients communicatively coupled to the central token management systemto identify a set of allowable token values unique to the client 100A(for instance, by eliminating any allowable token value assigned toanother client from consideration). The central token management system110 then sends 530 the generated set of unique allowable token values tothe client 100A. For example, the central token management system 110can assign the value range “21000000” to “21999999” to the client 100A,and can prevent any value within the range from being assigned toanother client as a possible token value. The client 100 stores 540 theset of unique allowable token values for subsequent use in generatingcandidate tokens.

The client 100A receives 550 sensitive data to be tokenized, and queries560 a token table associated with the client 100A with a portion of thesensitive data to determine if the token table includes a token mappedto the portion of sensitive data. If the token table includes a tokenmapped to the portion of the sensitive data, the sensitive data istokenized 580 using the token to create tokenized data. If the tokentable does not include a token mapped to the portion of the sensitivedata, the client 100A generates 570 a candidate token including a valuewithin the unique set of allowable token tables stored at the client100A and assigned by the central token management system 110. Thecandidate token and the portion of the sensitive data are stored 580 inthe token table associated with the client 100A and the sensitive datais tokenized 590 using the candidate token to create tokenized data.

Additional Configuration Considerations

The present invention has been described in particular detail withrespect to one possible embodiment. Those of skill in the art willappreciate that the invention may be practiced in other embodiments.First, the particular naming of the components and variables,capitalization of terms, the attributes, data structures, or any otherprogramming or structural aspect is not mandatory or significant, andthe mechanisms that implement the invention or its features may havedifferent names, formats, or protocols. Also, the particular division offunctionality between the various system components described herein ismerely exemplary, and not mandatory; functions performed by a singlesystem component may instead be performed by multiple components, andfunctions performed by multiple components may instead performed by asingle component.

Some portions of above description present the features of the presentinvention in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. These operations, while describedfunctionally or logically, are understood to be implemented by computerprograms. Furthermore, it has also proven convenient at times, to referto these arrangements of operations as modules or by functional names,without loss of generality.

Unless specifically stated otherwise as apparent from the abovediscussion, it is appreciated that throughout the description,discussions utilizing terms such as “determine” refer to the action andprocesses of a computer system, or similar electronic computing device,that manipulates and transforms data represented as physical(electronic) quantities within the computer system memories or registersor other such information storage, transmission or display devices.

Certain aspects of the present invention include process steps andinstructions described herein in the form of an algorithm. It should benoted that the process steps and instructions of the present inventioncould be embodied in software, firmware or hardware, and when embodiedin software, could be downloaded to reside on and be operated fromdifferent platforms used by real time network operating systems.

The present invention also relates to an apparatus for performing theoperations herein. This apparatus may be specially constructed for therequired purposes, or it may comprise a general-purpose computerselectively activated or reconfigured by a computer program stored on anon-transitory computer readable medium that can be accessed by thecomputer. Such a computer program may be stored in a computer readablestorage medium, such as, but is not limited to, any type of diskincluding floppy disks, optical disks, CD-ROMs, magnetic-optical disks,read-only memories (ROMs), random access memories (RAMs), EPROMs,EEPROMs, magnetic or optical cards, application specific integratedcircuits (ASICs), or any type of computer-readable storage mediumsuitable for storing electronic instructions, and each coupled to acomputer system bus. Furthermore, the computers referred to in thespecification may include a single processor or may be architecturesemploying multiple processor designs for increased computing capability.

The algorithms and operations presented herein are not inherentlyrelated to any particular computer or other apparatus. Variousgeneral-purpose systems may also be used with programs in accordancewith the teachings herein, or it may prove convenient to construct morespecialized apparatus to perform the required method steps. The requiredstructure for a variety of these systems will be apparent to those ofskill in the art, along with equivalent variations. In addition, thepresent invention is not described with reference to any particularprogramming language. It is appreciated that a variety of programminglanguages may be used to implement the teachings of the presentinvention as described herein, and any references to specific languagesare provided for invention of enablement and best mode of the presentinvention.

The present invention is well suited to a wide variety of computernetwork systems over numerous topologies. Within this field, theconfiguration and management of large networks comprise storage devicesand computers that are communicatively coupled to dissimilar computersand storage devices over a network, such as the Internet.

Finally, it should be noted that the language used in the specificationhas been principally selected for readability and instructionalpurposes, and may not have been selected to delineate or circumscribethe inventive subject matter. Accordingly, the disclosure of the presentinvention is intended to be illustrative, but not limiting, of the scopeof the invention, which is set forth in the following claims.

What is claimed is:
 1. A computer-implemented method for tokenizing datacomprising: generating, by a central token management system, a uniqueset of values for each of a plurality of clients communicatively coupledto the central token management system, the central token managementsystem configured to generating the unique sets of values to avoidcollisions between the plurality of clients; providing, by the centraltoken management system, each generated unique set of values to acorresponding client of the plurality of clients, each client configuredto generate one or more token values based on a value within the uniqueset of values corresponding to the client and to store the generatedtoken values in a token table mapping the generated token values tocorresponding input values; receiving, by the central token managementsystem, a request from a requesting client of the plurality of clientsfor an additional unique set of values; generating, by the central tokenmanagement system, the additional unique set of values to avoidcollisions with the previously generated unique sets of values; andproviding, by the central token management, the additional unique set ofvalues to the requesting client.
 2. The method of claim 1, wherein aclient, in response to a determination that a token table associatedwith the client includes a token value mapped to a value of a selectedportion of the data, is configured to tokenize the data using the tokenvalue mapped to the value of the selected portion of the data.
 3. Themethod of claim 1, wherein a client, in response to a determination thata token table associated with the client includes a token value for eachvalue in the unique set of values corresponding to the client, isconfigured to request an additional unique set of values from thecentral token management system.
 4. The method of claim 1, wherein thedata is one of: a credit card number, a bank account number, a socialsecurity number, a driver's license number, and a passport number. 5.The method of claim 1, wherein each unique set of values comprises anumeric range of values.
 6. The method of claim 1, wherein the centraltoken management system is further configured to periodically generateand provide a new unique set of values to each client.
 7. Anon-transitory computer-readable medium storing executable computerinstructions for tokenizing data, the instructions, when executed by ahardware processor, configured to perform steps comprising: generating,by a central token management system, a unique set of values for each ofa plurality of clients communicatively coupled to the central tokenmanagement system, the central token management system configured togenerating the unique sets of values to avoid collisions between theplurality of clients; providing, by the central token management system,each generated unique set of values to a corresponding client of theplurality of clients, each client configured to generate one or moretoken values based on a value within the unique set of valuescorresponding to the client and to store the generated token values in atoken table mapping the generated token values to corresponding inputvalues; receiving, by the central token management system, a requestfrom a requesting client of the plurality of clients for an additionalunique set of values; generating, by the central token managementsystem, the additional unique set of values to avoid collisions with thepreviously generated unique sets of values; and providing, by thecentral token management, the additional unique set of values to therequesting client.
 8. The computer-readable medium of claim 7, wherein aclient, in response to a determination that a token table associatedwith a client includes a token value mapped to a value of a selectedportion of the data, is configured to tokenize the data using the tokenvalue mapped to the value of the selected portion of the data.
 9. Thecomputer-readable medium of claim 7, wherein a client, in response to adetermination that a token table associated with the client includes atoken value for each value in the unique set of values corresponding tothe client, is configured to request an additional unique set of valuesfrom the central token management system.
 10. The computer-readablemedium of claim 7, wherein the data is one of: a credit card number, abank account number, a social security number, a driver's licensenumber, and a passport number.
 11. The computer-readable medium of claim7, wherein each unique set of values comprises a numeric range ofvalues.
 12. The computer-readable medium of claim 7, wherein the centraltoken management system is further configured to periodically generateand provide a new unique set of values to each client.
 13. A system fortokenizing data comprising: a plurality of client devices; and a centraltoken management system communicatively coupled to the plurality ofclient devices and configured to perform steps comprising: generating aunique set of values for each of the plurality of client devices, thecentral token management system configured to generating the unique setsof values to avoid collisions between the plurality of client devices;providing each generated unique set of values to a corresponding clientdevice of the plurality of client devices, each client device configuredto generate one or more token values based on a value within the uniqueset of values corresponding to the client device and to store thegenerated token values in a token table mapping the generated tokenvalues to corresponding input values; receiving a request from arequesting client device of the plurality of client devices for anadditional unique set of values; generating the additional unique set ofvalues to avoid collisions with the previously generated unique sets ofvalues; and providing the additional unique set of values to therequesting client device.
 14. The system of claim 13, wherein a clientdevice, in response to a determination that a token table associatedwith the client device includes a token value mapped to a value of aselected portion of the data, is configured to tokenize the data usingthe token value mapped to the value of the selected portion of the data.15. The system of claim 13, wherein a client device, in response to adetermination that a token table associated with the client deviceincludes a token value for each value in the unique set of valuescorresponding to the client, is configured to request an additionalunique set of values from the central token management system.
 16. Thesystem of claim 13, wherein the data is one of: a credit card number, abank account number, a social security number, a driver's licensenumber, and a passport number.
 17. The system of claim 13, wherein eachunique set of values comprises a numeric range of values.
 18. The systemof claim 13, wherein the central token management system is furtherconfigured to periodically generate and provide a new unique set ofvalues to each client device.